code: def non_uniform_errors(f, num, ndim, label=None):
      """Build DataFrame of approximation errors with non uniform grid."""
      points = non_uniform_grid(np.power(num, ndim), ndim)
      values = f(points)
      approx_all = non_uniform_approx_nearest(points, values)
  
      def name_errors():
          for (ds, name), approx in zip(
              derivative_names(ndim), approx_all.T
          ):
              actual = autograd(f, ds, points)
              yield name, np.abs(actual - approx)
  
      return _build_errors_df(name_errors(), label)
  
file_path: tf-quant-finance/tf_quant_finance/experimental/finite_difference/methods.py
imports: from autograd import elementwise_grad
  import autograd.numpy
  import pandas
  import sobol_seq
label_desc: Use image node_id 11 for calling a global function with example usage: non_uniform_errors(f, num, ndim, label) and returns: _build_errors_df